{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# CAPPI插值示例\n",
    "要求pycwr版本>=0.2.15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from pycwr.io import read_auto\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import cartopy.crs as ccrs\n",
    "from pycwr.draw.RadarPlot import plot_xy, Graph, plot_lonlat_map, GraphMap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据部分\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "PRD = read_auto(\"/Users/zhengyu/OneDrive/Work/13_天气雷达库_pycwr/test_data/Z9040.20190905.175751.AR2.bz2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:    (range: 2400, time: 729)\n",
       "Coordinates:\n",
       "    azimuth    (time) float64 133.4 133.9 134.4 134.9 ... 132.7 133.2 133.7\n",
       "    elevation  (time) float64 0.02 0.02 0.02 0.02 0.02 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    x          (time, range) float64 90.73 181.5 272.2 ... 2.168e+05 2.169e+05\n",
       "    y          (time, range) float64 -85.95 -171.9 ... -2.069e+05 -2.07e+05\n",
       "    z          (time, range) float64 3.024e+03 3.024e+03 ... 8.314e+03 8.319e+03\n",
       "    lat        (time, range) float64 30.03 30.03 30.03 ... 28.15 28.15 28.15\n",
       "    lon        (time, range) float64 119.0 119.0 119.0 ... 121.2 121.2 121.2\n",
       "  * range      (range) float64 125.0 250.0 375.0 ... 2.998e+05 2.999e+05 3e+05\n",
       "  * time       (time) datetime64[ns] 2019-09-05T17:58:32.575950 ... 2019-09-0...\n",
       "Data variables:\n",
       "    V          (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    W          (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    dBT        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    dBZ        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    SQI        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    CPA        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    ZDR        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    CC         (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    PhiDP      (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    KDP        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    SNRH       (time, range) float64 nan nan nan nan nan ... -3.0 nan nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-42903199-8c1f-4460-a78a-61f76da341c9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-42903199-8c1f-4460-a78a-61f76da341c9' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>range</span>: 2400</li><li><span class='xr-has-index'>time</span>: 729</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-90e86b6a-9ca1-40e8-97d0-eceeb23d3e6a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-90e86b6a-9ca1-40e8-97d0-eceeb23d3e6a' class='xr-section-summary' >Coordinates: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>azimuth</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>133.4 133.9 134.4 ... 133.2 133.7</div><input id='attrs-0460847f-4246-45f4-943a-6b9f2928b4ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0460847f-4246-45f4-943a-6b9f2928b4ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1090a33e-da51-4db8-a994-5097d41e1e1c' class='xr-var-data-in' type='checkbox'><label for='data-1090a33e-da51-4db8-a994-5097d41e1e1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>standard_name :</span></dt><dd>beam_azimuth_angle</dd><dt><span>long_name :</span></dt><dd>azimuth_angle_from_true_north</dd><dt><span>axis :</span></dt><dd>radial_azimuth_coordinate</dd><dt><span>comment :</span></dt><dd>Azimuth of antenna relative to true north</dd></dl></div><div class='xr-var-data'><pre>array([1.33449997e+02, 1.33949997e+02, 1.34440002e+02, 1.34940002e+02,\n",
       "       1.35440002e+02, 1.35940002e+02, 1.36449997e+02, 1.36949997e+02,\n",
       "       1.37470001e+02, 1.37990005e+02, 1.38500000e+02, 1.39009995e+02,\n",
       "       1.39520004e+02, 1.40020004e+02, 1.40529999e+02, 1.41039993e+02,\n",
       "       1.41559998e+02, 1.42100006e+02, 1.42589996e+02, 1.43089996e+02,\n",
       "       1.43589996e+02, 1.44070007e+02, 1.44589996e+02, 1.45100006e+02,\n",
       "       1.45619995e+02, 1.46139999e+02, 1.46649994e+02, 1.47139999e+02,\n",
       "       1.47630005e+02, 1.48110001e+02, 1.48630005e+02, 1.49119995e+02,\n",
       "       1.49639999e+02, 1.50149994e+02, 1.50649994e+02, 1.51139999e+02,\n",
       "       1.51639999e+02, 1.52130005e+02, 1.52639999e+02, 1.53130005e+02,\n",
       "       1.53619995e+02, 1.54139999e+02, 1.54639999e+02, 1.55130005e+02,\n",
       "       1.55619995e+02, 1.56080002e+02, 1.56580002e+02, 1.57080002e+02,\n",
       "       1.57559998e+02, 1.58080002e+02, 1.58570007e+02, 1.59059998e+02,\n",
       "       1.59539993e+02, 1.60050003e+02, 1.60509995e+02, 1.61029999e+02,\n",
       "       1.61529999e+02, 1.62039993e+02, 1.62550003e+02, 1.63039993e+02,\n",
       "       1.63529999e+02, 1.64029999e+02, 1.64500000e+02, 1.65009995e+02,\n",
       "       1.65500000e+02, 1.66020004e+02, 1.66509995e+02, 1.67009995e+02,\n",
       "       1.67500000e+02, 1.67990005e+02, 1.68460007e+02, 1.68960007e+02,\n",
       "       1.69460007e+02, 1.69949997e+02, 1.70470001e+02, 1.70949997e+02,\n",
       "       1.71449997e+02, 1.71940002e+02, 1.72419998e+02, 1.72910004e+02,\n",
       "...\n",
       "       9.60999985e+01, 9.65699997e+01, 9.70899963e+01, 9.75800018e+01,\n",
       "       9.80500031e+01, 9.85599976e+01, 9.90500031e+01, 9.95599976e+01,\n",
       "       1.00040001e+02, 1.00519997e+02, 1.01019997e+02, 1.01529999e+02,\n",
       "       1.02029999e+02, 1.02510002e+02, 1.03000000e+02, 1.03489998e+02,\n",
       "       1.04000000e+02, 1.04470001e+02, 1.04970001e+02, 1.05480003e+02,\n",
       "       1.05970001e+02, 1.06470001e+02, 1.06940002e+02, 1.07449997e+02,\n",
       "       1.07949997e+02, 1.08419998e+02, 1.08930000e+02, 1.09440002e+02,\n",
       "       1.09919998e+02, 1.10410004e+02, 1.10900002e+02, 1.11379997e+02,\n",
       "       1.11900002e+02, 1.12379997e+02, 1.12879997e+02, 1.13400002e+02,\n",
       "       1.13879997e+02, 1.14379997e+02, 1.14860001e+02, 1.15370003e+02,\n",
       "       1.15860001e+02, 1.16360001e+02, 1.16839996e+02, 1.17339996e+02,\n",
       "       1.17849998e+02, 1.18349998e+02, 1.18820000e+02, 1.19330002e+02,\n",
       "       1.19820000e+02, 1.20300003e+02, 1.20809998e+02, 1.21309998e+02,\n",
       "       1.21820000e+02, 1.22309998e+02, 1.22769997e+02, 1.23290001e+02,\n",
       "       1.23779999e+02, 1.24279999e+02, 1.24769997e+02, 1.25269997e+02,\n",
       "       1.25769997e+02, 1.26269997e+02, 1.26739998e+02, 1.27250000e+02,\n",
       "       1.27730003e+02, 1.28229996e+02, 1.28729996e+02, 1.29220001e+02,\n",
       "       1.29740005e+02, 1.30229996e+02, 1.30710007e+02, 1.31199997e+02,\n",
       "       1.31690002e+02, 1.32179993e+02, 1.32679993e+02, 1.33160004e+02,\n",
       "       1.33669998e+02])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>elevation</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.02 0.02 0.02 0.02 ... 0.0 0.0 0.0</div><input id='attrs-fb1f0f24-6d2f-450a-b9ec-0113ae72c498' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb1f0f24-6d2f-450a-b9ec-0113ae72c498' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f4d7df1-d290-4870-84d2-0f250265db42' class='xr-var-data-in' type='checkbox'><label for='data-2f4d7df1-d290-4870-84d2-0f250265db42' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>standard_name :</span></dt><dd>beam_elevation_angle</dd><dt><span>long_name :</span></dt><dd>elevation_angle_from_horizontal_plane</dd><dt><span>axis :</span></dt><dd>radial_elevation_coordinate</dd><dt><span>comment :</span></dt><dd>Elevation of antenna relative to the horizontal plane</dd></dl></div><div class='xr-var-data'><pre>array([ 0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "        0.02      ,  0.02      ,  0.02      ,  0.02      ,  0.02      ,\n",
       "...\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ,  0.        ,\n",
       "        0.        ,  0.        ,  0.        ,  0.        ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>90.73 181.5 ... 2.168e+05 2.169e+05</div><input id='attrs-ff36d0e5-b7b6-40d0-b6cb-8b2d12b3322b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff36d0e5-b7b6-40d0-b6cb-8b2d12b3322b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-867a88c6-ad53-46fa-808a-c5f794ad2362' class='xr-var-data-in' type='checkbox'><label for='data-867a88c6-ad53-46fa-808a-c5f794ad2362' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>distance from radar in east</dd><dt><span>standard_name :</span></dt><dd>distance in x</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[9.07306987e+01, 1.81461396e+02, 2.72192093e+02, ...,\n",
       "        2.17479336e+05, 2.17569952e+05, 2.17660567e+05],\n",
       "       [8.99771995e+01, 1.79954398e+02, 2.69931596e+02, ...,\n",
       "        2.15673216e+05, 2.15763079e+05, 2.15852942e+05],\n",
       "       [8.92321136e+01, 1.78464226e+02, 2.67696338e+02, ...,\n",
       "        2.13887263e+05, 2.13976382e+05, 2.14065501e+05],\n",
       "       ...,\n",
       "       [9.18775663e+01, 1.83755132e+02, 2.75632699e+02, ...,\n",
       "        2.20231059e+05, 2.20322822e+05, 2.20414586e+05],\n",
       "       [9.11645620e+01, 1.82329124e+02, 2.73493686e+02, ...,\n",
       "        2.18521984e+05, 2.18613035e+05, 2.18704086e+05],\n",
       "       [9.04000111e+01, 1.80800022e+02, 2.71200033e+02, ...,\n",
       "        2.16689351e+05, 2.16779638e+05, 2.16869926e+05]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-85.95 -171.9 ... -2.07e+05</div><input id='attrs-11b669af-0df0-4195-902f-fc3ac85fab35' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11b669af-0df0-4195-902f-fc3ac85fab35' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff329a29-dc32-484b-8b26-43af381f86f1' class='xr-var-data-in' type='checkbox'><label for='data-ff329a29-dc32-484b-8b26-43af381f86f1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>distance from radar in north</dd><dt><span>standard_name :</span></dt><dd>distance in y</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[-8.59498541e+01, -1.71899707e+02, -2.57849559e+02, ...,\n",
       "        -2.06019764e+05, -2.06105605e+05, -2.06191446e+05],\n",
       "       [-8.67383460e+01, -1.73476691e+02, -2.60215035e+02, ...,\n",
       "        -2.07909761e+05, -2.07996389e+05, -2.08083018e+05],\n",
       "       [-8.75046685e+01, -1.75009336e+02, -2.62514003e+02, ...,\n",
       "        -2.09746618e+05, -2.09834011e+05, -2.09921405e+05],\n",
       "       ...,\n",
       "       [-8.47227950e+01, -1.69445590e+02, -2.54168385e+02, ...,\n",
       "        -2.03081031e+05, -2.03165648e+05, -2.03250265e+05],\n",
       "       [-8.54895421e+01, -1.70979084e+02, -2.56468626e+02, ...,\n",
       "        -2.04918928e+05, -2.05004311e+05, -2.05089694e+05],\n",
       "       [-8.62976081e+01, -1.72595216e+02, -2.58892824e+02, ...,\n",
       "        -2.06855867e+05, -2.06942057e+05, -2.07028247e+05]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.024e+03 3.024e+03 ... 8.319e+03</div><input id='attrs-b6454fd5-2829-4bfb-b6d7-d7b896513506' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b6454fd5-2829-4bfb-b6d7-d7b896513506' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f54cce38-092d-4b35-a49a-9fe3215dd31d' class='xr-var-data-in' type='checkbox'><label for='data-f54cce38-092d-4b35-a49a-9fe3215dd31d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>sea surface level</dd><dt><span>standard_name :</span></dt><dd>altitude in z</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>units :</span></dt><dd>meters</dd></dl></div><div class='xr-var-data'><pre>array([[3024.04455276, 3024.09094458, 3024.13917547, ..., 8414.59735641,\n",
       "        8419.04915432, 8423.5027878 ],\n",
       "       [3024.04455276, 3024.09094458, 3024.13917547, ..., 8414.59735641,\n",
       "        8419.04915432, 8423.5027878 ],\n",
       "       [3024.04455276, 3024.09094458, 3024.13917547, ..., 8414.59735641,\n",
       "        8419.04915432, 8423.5027878 ],\n",
       "       ...,\n",
       "       [3024.00091953, 3024.00367812, 3024.00827578, ..., 8310.03057355,\n",
       "        8314.43882015, 8318.84890237],\n",
       "       [3024.00091953, 3024.00367812, 3024.00827578, ..., 8310.03057355,\n",
       "        8314.43882015, 8318.84890237],\n",
       "       [3024.00091953, 3024.00367812, 3024.00827578, ..., 8310.03057355,\n",
       "        8314.43882015, 8318.84890237]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>30.03 30.03 30.03 ... 28.15 28.15</div><input id='attrs-6446aaef-e1c4-436d-8231-dc3edaee9759' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6446aaef-e1c4-436d-8231-dc3edaee9759' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43885ad8-f4c0-4ad3-833d-8d550de7cc74' class='xr-var-data-in' type='checkbox'><label for='data-43885ad8-f4c0-4ad3-833d-8d550de7cc74' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([[30.02783726, 30.02706428, 30.0262913 , ..., 28.15723806,\n",
       "        28.15645087, 28.15566367],\n",
       "       [30.02783017, 30.0270501 , 30.02627003, ..., 28.1405545 ,\n",
       "        28.13976049, 28.13896647],\n",
       "       [30.02782328, 30.02703632, 30.02624935, ..., 28.12434252,\n",
       "        28.12354187, 28.12274122],\n",
       "       ...,\n",
       "       [30.0278483 , 30.02708635, 30.02632441, ..., 28.18318342,\n",
       "        28.18240683, 28.18163023],\n",
       "       [30.0278414 , 30.02707256, 30.02630372, ..., 28.16695579,\n",
       "        28.16617256, 28.16538933],\n",
       "       [30.02783413, 30.02705803, 30.02628192, ..., 28.14985635,\n",
       "        28.14906612, 28.14827589]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>119.0 119.0 119.0 ... 121.2 121.2</div><input id='attrs-4a864314-22f4-4a03-9a55-ff18cc677ca9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a864314-22f4-4a03-9a55-ff18cc677ca9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a166e50-de58-4d40-b1f6-dd776d3a4421' class='xr-var-data-in' type='checkbox'><label for='data-6a166e50-de58-4d40-b1f6-dd776d3a4421' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([[119.00288795, 119.00383039, 119.00477282, ..., 121.22005283,\n",
       "        121.22096049, 121.22186813],\n",
       "       [119.00288012, 119.00381474, 119.00474934, ..., 121.20127998,\n",
       "        121.20217982, 121.20307965],\n",
       "       [119.00287238, 119.00379926, 119.00472612, ..., 121.18272872,\n",
       "        121.18362084, 121.18451294],\n",
       "       ...,\n",
       "       [119.00289986, 119.00385422, 119.00480856, ..., 121.24867744,\n",
       "        121.24959704, 121.25051662],\n",
       "       [119.00289246, 119.0038394 , 119.00478634, ..., 121.23089478,\n",
       "        121.23180696, 121.23271914],\n",
       "       [119.00288452, 119.00382352, 119.00476251, ..., 121.21183917,\n",
       "        121.21274342, 121.21364765]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>range</span></div><div class='xr-var-dims'>(range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>125.0 250.0 ... 2.999e+05 3e+05</div><input id='attrs-fed26887-fd56-4586-be5e-6a49ac6fa7f0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fed26887-fd56-4586-be5e-6a49ac6fa7f0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aae41036-882e-4a54-9316-e128e61d5c68' class='xr-var-data-in' type='checkbox'><label for='data-aae41036-882e-4a54-9316-e128e61d5c68' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>projection_range_coordinate</dd><dt><span>long_name :</span></dt><dd>range_to_measurement_volume</dd><dt><span>axis :</span></dt><dd>radial_range_coordinate</dd><dt><span>spacing_is_constant :</span></dt><dd>true</dd><dt><span>comment :</span></dt><dd>Coordinate variable for range. Range to center of each bin.</dd></dl></div><div class='xr-var-data'><pre>array([1.25000e+02, 2.50000e+02, 3.75000e+02, ..., 2.99750e+05, 2.99875e+05,\n",
       "       3.00000e+05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-09-05T17:58:32.575950 ... 2...</div><input id='attrs-742bef56-316a-45a3-80ae-e83af3c43499' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-742bef56-316a-45a3-80ae-e83af3c43499' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a68fb90c-c73b-429a-a554-a9399776afa4' class='xr-var-data-in' type='checkbox'><label for='data-a68fb90c-c73b-429a-a554-a9399776afa4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>long_name :</span></dt><dd>time_in_seconds_since_volume_start</dd><dt><span>calendar :</span></dt><dd>gregorian</dd><dt><span>comment :</span></dt><dd>Coordinate variable for time. Time at the center of each ray, in fractional seconds since the global variable time_coverage_start</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-09-05T17:58:32.575950000&#x27;, &#x27;2019-09-05T17:58:32.625457000&#x27;,\n",
       "       &#x27;2019-09-05T17:58:32.674899000&#x27;, ..., &#x27;2019-09-05T17:59:08.457581000&#x27;,\n",
       "       &#x27;2019-09-05T17:59:08.506782000&#x27;, &#x27;2019-09-05T17:59:08.556089000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b870b63d-355f-49bd-aa9f-b97e20578d8f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b870b63d-355f-49bd-aa9f-b97e20578d8f' class='xr-section-summary' >Data variables: <span>(11)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>V</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-45f5e590-be89-4991-b0a1-d0a942faa1d0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-45f5e590-be89-4991-b0a1-d0a942faa1d0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-133297c1-5798-43e7-8897-4fd1b35cc292' class='xr-var-data-in' type='checkbox'><label for='data-133297c1-5798-43e7-8897-4fd1b35cc292' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters_per_second</dd><dt><span>standard_name :</span></dt><dd>radial_velocity_of_scatterers_away_from_instrument</dd><dt><span>long_name :</span></dt><dd>Mean dopper velocity</dd><dt><span>valid_max :</span></dt><dd>50.0</dd><dt><span>valid_min :</span></dt><dd>-50.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>W</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c2ae591a-ce8d-45e1-8bc6-b9152b75d8f3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c2ae591a-ce8d-45e1-8bc6-b9152b75d8f3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1e3ae02c-e665-4cc1-b96f-2a567df94570' class='xr-var-data-in' type='checkbox'><label for='data-1e3ae02c-e665-4cc1-b96f-2a567df94570' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters_per_second</dd><dt><span>standard_name :</span></dt><dd>doppler_spectrum_width</dd><dt><span>long_name :</span></dt><dd>Doppler spectrum width</dd><dt><span>valid_max :</span></dt><dd>30.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dBT</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-9147dace-6806-42d7-8114-289b21f56792' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9147dace-6806-42d7-8114-289b21f56792' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea621f47-6df0-4c38-88e4-82ef335ed38f' class='xr-var-data-in' type='checkbox'><label for='data-ea621f47-6df0-4c38-88e4-82ef335ed38f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>Total power</dd><dt><span>valid_max :</span></dt><dd>80.0</dd><dt><span>valid_min :</span></dt><dd>-30.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dBZ</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-bb6932df-eded-4dfd-9693-b637c72d0b13' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb6932df-eded-4dfd-9693-b637c72d0b13' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6f0b3085-c317-49ca-9e6c-e3f0e537a10e' class='xr-var-data-in' type='checkbox'><label for='data-6f0b3085-c317-49ca-9e6c-e3f0e537a10e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>standard_name :</span></dt><dd>equivalent_reflectivity_factor</dd><dt><span>long_name :</span></dt><dd>Reflectivity</dd><dt><span>valid_max :</span></dt><dd>80.0</dd><dt><span>valid_min :</span></dt><dd>-30.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SQI</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1e82ac21-1312-4ead-8974-68b8cc21cfb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e82ac21-1312-4ead-8974-68b8cc21cfb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cab6012c-edff-436a-a22e-14ee95b58b47' class='xr-var-data-in' type='checkbox'><label for='data-cab6012c-edff-436a-a22e-14ee95b58b47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ratio</dd><dt><span>standard_name :</span></dt><dd>normalized_coherent_power</dd><dt><span>long_name :</span></dt><dd>Normalized coherent power</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>comment :</span></dt><dd>Also know as signal quality index (SQI)</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CPA</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-7aa2aa66-113f-4319-b1c1-33813e24230f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7aa2aa66-113f-4319-b1c1-33813e24230f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ee61368-5320-432a-bd3f-9caa67ff3ac8' class='xr-var-data-in' type='checkbox'><label for='data-7ee61368-5320-432a-bd3f-9caa67ff3ac8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ratio</dd><dt><span>standard_name :</span></dt><dd>clutter_phase_alignment</dd><dt><span>long_name :</span></dt><dd>clutter phase alignment</dd><dt><span>valid_max :</span></dt><dd>0</dd><dt><span>valid_min :</span></dt><dd>1</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ZDR</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-d35e510d-b178-4b33-b5c4-94f710b7d8bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d35e510d-b178-4b33-b5c4-94f710b7d8bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe8d875d-7b64-4a6f-a6b0-5bf4693496a8' class='xr-var-data-in' type='checkbox'><label for='data-fe8d875d-7b64-4a6f-a6b0-5bf4693496a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dB</dd><dt><span>standard_name :</span></dt><dd>log_differential_reflectivity_hv</dd><dt><span>long_name :</span></dt><dd>Differential reflectivity</dd><dt><span>valid_max :</span></dt><dd>8.0</dd><dt><span>valid_min :</span></dt><dd>-2.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CC</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-ea83c02a-37fe-4319-a827-28c17dc4bbe9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea83c02a-37fe-4319-a827-28c17dc4bbe9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e200cbc7-fb24-4962-bcd8-2a402cee6025' class='xr-var-data-in' type='checkbox'><label for='data-e200cbc7-fb24-4962-bcd8-2a402cee6025' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>ratio</dd><dt><span>standard_name :</span></dt><dd>cross_correlation_ratio_hv</dd><dt><span>long_name :</span></dt><dd>Cross correlation ratio (RHOHV)</dd><dt><span>valid_max :</span></dt><dd>1.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PhiDP</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-306f0a06-d5c5-4bf3-8af4-a1b0f93d0afa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-306f0a06-d5c5-4bf3-8af4-a1b0f93d0afa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3b5ee36a-82c8-47f2-b3d5-3898784bee16' class='xr-var-data-in' type='checkbox'><label for='data-3b5ee36a-82c8-47f2-b3d5-3898784bee16' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>standard_name :</span></dt><dd>differential_phase_hv</dd><dt><span>long_name :</span></dt><dd>Differential phase (PhiDP)</dd><dt><span>valid_max :</span></dt><dd>360.0</dd><dt><span>valid_min :</span></dt><dd>0.0</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KDP</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-f5aa4d72-50ea-4152-883f-ccbb4cb07eb1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5aa4d72-50ea-4152-883f-ccbb4cb07eb1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8e4315c8-260f-48a0-a6c8-f33d41d27b5f' class='xr-var-data-in' type='checkbox'><label for='data-8e4315c8-260f-48a0-a6c8-f33d41d27b5f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees/km</dd><dt><span>standard_name :</span></dt><dd>specific_differential_phase_hv</dd><dt><span>long_name :</span></dt><dd>Specific differential phase (KDP)</dd><dt><span>valid_max :</span></dt><dd>5</dd><dt><span>valid_min :</span></dt><dd>-2</dd><dt><span>coordinates :</span></dt><dd>elevation azimuth range</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SNRH</span></div><div class='xr-var-dims'>(time, range)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan</div><input id='attrs-9f757209-8f13-41d3-b94e-2d7bce60d3f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f757209-8f13-41d3-b94e-2d7bce60d3f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-92506ad7-8d34-4708-a2fc-006640637b58' class='xr-var-data-in' type='checkbox'><label for='data-92506ad7-8d34-4708-a2fc-006640637b58' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>horizontal signal noise ratio</dd></dl></div><div class='xr-var-data'><pre>array([[ nan,  nan,  nan, ..., -2. , -4.5, -7.5],\n",
       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan],\n",
       "       ...,\n",
       "       [ nan,  nan,  nan, ...,  nan, -7.5,  nan],\n",
       "       [ nan,  nan,  nan, ..., -2. , -4.5, -7.5],\n",
       "       [ nan,  nan,  nan, ...,  nan,  nan,  nan]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-481f831c-3b8b-4081-8f78-734f39819893' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-481f831c-3b8b-4081-8f78-734f39819893' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:    (range: 2400, time: 729)\n",
       "Coordinates:\n",
       "    azimuth    (time) float64 133.4 133.9 134.4 134.9 ... 132.7 133.2 133.7\n",
       "    elevation  (time) float64 0.02 0.02 0.02 0.02 0.02 ... 0.0 0.0 0.0 0.0 0.0\n",
       "    x          (time, range) float64 90.73 181.5 272.2 ... 2.168e+05 2.169e+05\n",
       "    y          (time, range) float64 -85.95 -171.9 ... -2.069e+05 -2.07e+05\n",
       "    z          (time, range) float64 3.024e+03 3.024e+03 ... 8.314e+03 8.319e+03\n",
       "    lat        (time, range) float64 30.03 30.03 30.03 ... 28.15 28.15 28.15\n",
       "    lon        (time, range) float64 119.0 119.0 119.0 ... 121.2 121.2 121.2\n",
       "  * range      (range) float64 125.0 250.0 375.0 ... 2.998e+05 2.999e+05 3e+05\n",
       "  * time       (time) datetime64[ns] 2019-09-05T17:58:32.575950 ... 2019-09-0...\n",
       "Data variables:\n",
       "    V          (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    W          (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    dBT        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    dBZ        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    SQI        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    CPA        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    ZDR        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    CC         (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    PhiDP      (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    KDP        (time, range) float64 nan nan nan nan nan ... nan nan nan nan nan\n",
       "    SNRH       (time, range) float64 nan nan nan nan nan ... -3.0 nan nan nan"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PRD.fields[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 根据距离雷达中心的x和y生成cappi数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "x1d = np.arange(-200000, 200001, 1000) ##x方向1km等间距， -200km～200km范围\n",
    "y1d = np.arange(-200000, 200001, 1000) ##y方向1km等间距， -200km～200km范围\n",
    "PRD.add_product_CAPPI_xy(XRange=x1d, YRange=y1d, level_height=1500) ##插值1500m高度的\n",
    "#XRange: np.ndarray, 1d, units:meters\n",
    "# YRange: np.ndarray, 1d, units:meters\n",
    "# level_height: 要插值的高度，常量, units:meters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:       (x_cappi_1500: 401, y_cappi_1500: 401)\n",
       "Coordinates:\n",
       "  * x_cappi_1500  (x_cappi_1500) int64 -200000 -199000 -198000 ... 199000 200000\n",
       "  * y_cappi_1500  (y_cappi_1500) int64 -200000 -199000 -198000 ... 199000 200000\n",
       "Data variables:\n",
       "    CAPPI_1500    (x_cappi_1500, y_cappi_1500) float64 nan nan nan ... nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b1245ddb-aa42-421f-80f7-6469cb1ecf8d' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b1245ddb-aa42-421f-80f7-6469cb1ecf8d' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x_cappi_1500</span>: 401</li><li><span class='xr-has-index'>y_cappi_1500</span>: 401</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-18aa9522-cda5-4344-8541-961cacfcaf87' class='xr-section-summary-in' type='checkbox'  checked><label for='section-18aa9522-cda5-4344-8541-961cacfcaf87' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_cappi_1500</span></div><div class='xr-var-dims'>(x_cappi_1500)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-200000 -199000 ... 199000 200000</div><input id='attrs-7d5c0baa-b800-49a9-8136-df29377669a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d5c0baa-b800-49a9-8136-df29377669a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b47a95f-6bcf-4758-93b4-07d8dfc19230' class='xr-var-data-in' type='checkbox'><label for='data-0b47a95f-6bcf-4758-93b4-07d8dfc19230' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>CAPPI_product_x_axis </dd><dt><span>long_name :</span></dt><dd>east_distance_from_radar</dd><dt><span>axis :</span></dt><dd>xy_coordinate</dd><dt><span>comment :</span></dt><dd>Distance from radar in east</dd></dl></div><div class='xr-var-data'><pre>array([-200000, -199000, -198000, ...,  198000,  199000,  200000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_cappi_1500</span></div><div class='xr-var-dims'>(y_cappi_1500)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-200000 -199000 ... 199000 200000</div><input id='attrs-0d104430-d83b-404a-9455-63e38a1d05ee' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d104430-d83b-404a-9455-63e38a1d05ee' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5471f9a-5dc4-4b7b-aa51-c8109ed5d110' class='xr-var-data-in' type='checkbox'><label for='data-e5471f9a-5dc4-4b7b-aa51-c8109ed5d110' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>CAPPI_product_y_axis </dd><dt><span>long_name :</span></dt><dd>north_distance_from_radar</dd><dt><span>axis :</span></dt><dd>xy_coordinate</dd><dt><span>comment :</span></dt><dd>Distance from radar in north</dd></dl></div><div class='xr-var-data'><pre>array([-200000, -199000, -198000, ...,  198000,  199000,  200000])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-85296979-ae61-4cb6-98d0-45c593208d41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-85296979-ae61-4cb6-98d0-45c593208d41' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAPPI_1500</span></div><div class='xr-var-dims'>(x_cappi_1500, y_cappi_1500)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-fde3f717-27fd-440e-9bb5-ee1dda818507' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fde3f717-27fd-440e-9bb5-ee1dda818507' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da76141f-2d13-4d86-b9eb-a8183e92f6bb' class='xr-var-data-in' type='checkbox'><label for='data-da76141f-2d13-4d86-b9eb-a8183e92f6bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>standard_name :</span></dt><dd>Constant_altitude_plan_position_indicator</dd><dt><span>long_name :</span></dt><dd>Constant_altitude_plan_position_indicator</dd><dt><span>axis :</span></dt><dd>xy_coordinate</dd><dt><span>comment :</span></dt><dd>CAPPI of level 1500 m.</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cbcba3a9-6d5b-46c7-b36c-6f35bd6b12ae' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-cbcba3a9-6d5b-46c7-b36c-6f35bd6b12ae' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
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      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:       (x_cappi_1500: 401, y_cappi_1500: 401)\n",
       "Coordinates:\n",
       "  * x_cappi_1500  (x_cappi_1500) int64 -200000 -199000 -198000 ... 199000 200000\n",
       "  * y_cappi_1500  (y_cappi_1500) int64 -200000 -199000 -198000 ... 199000 200000\n",
       "Data variables:\n",
       "    CAPPI_1500    (x_cappi_1500, y_cappi_1500) float64 nan nan nan ... nan nan"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PRD.product ##可以查看1500m的cappi的产品"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/zhengyu/anaconda3/envs/pycwr/lib/python3.9/site-packages/pycwr-0.2.15-py3.9-macosx-10.9-x86_64.egg/pycwr/draw/RadarPlot.py:602: MatplotlibDeprecationWarning: shading='flat' when X and Y have the same dimensions as C is deprecated since 3.3.  Either specify the corners of the quadrilaterals with X and Y, or pass shading='auto', 'nearest' or 'gouraud', or set rcParams['pcolor.shading'].  This will become an error two minor releases later.\n",
      "  gci = ax.pcolormesh(x / 1000., y / 1000., data, cmap=cmaps, \\\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f9bf03b9310>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid_x, grid_y = np.meshgrid(x1d, y1d, indexing=\"ij\")\n",
    "fig, ax = plt.subplots()\n",
    "plot_xy(ax, grid_x, grid_y, PRD.product.CAPPI_1500) ##画图显示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#显示 0.5度仰角进行对比\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "graph = Graph(PRD)\n",
    "graph.plot_ppi(ax, 0, \"dBZ\", cmap=\"CN_ref\") ## 0代表第一层, dBZ代表反射率产品，cmap\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 根据经纬度信息生成cappi数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "lon1d = np.arange(117, 121.0001, 0.01) ##lon方向0.01等间距，117-121 范围\n",
    "lat1d = np.arange(28, 32.0001, 0.01) ##lat方向0.01等间距， 28～32度范围\n",
    "PRD.add_product_CAPPI_lonlat(XLon=lon1d, YLat=lat1d, level_height=1500) ##插值1500m高度的\n",
    "# XLon:np.ndarray, 1d, units:degrees\n",
    "# YLat:np.ndarray, 1d, units:degrees\n",
    "# level_height:常量，要计算的高度 units:meters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<defs>\n",
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       "\n",
       ".xr-attrs dt, dd {\n",
       "  padding: 0;\n",
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       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:         (lat_cappi_1500: 401, lon_cappi_1500: 401, x_cappi_1500: 401, y_cappi_1500: 401)\n",
       "Coordinates:\n",
       "  * x_cappi_1500    (x_cappi_1500) int64 -200000 -199000 ... 199000 200000\n",
       "  * y_cappi_1500    (y_cappi_1500) int64 -200000 -199000 ... 199000 200000\n",
       "  * lon_cappi_1500  (lon_cappi_1500) float64 117.0 117.0 117.0 ... 121.0 121.0\n",
       "  * lat_cappi_1500  (lat_cappi_1500) float64 28.0 28.01 28.02 ... 31.99 32.0\n",
       "Data variables:\n",
       "    CAPPI_1500      (x_cappi_1500, y_cappi_1500) float64 nan nan nan ... nan nan\n",
       "    CAPPI_geo_1500  (lon_cappi_1500, lat_cappi_1500) float64 nan nan ... nan nan</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-eeabeb38-a976-416b-86f2-2490e93469cb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-eeabeb38-a976-416b-86f2-2490e93469cb' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>lat_cappi_1500</span>: 401</li><li><span class='xr-has-index'>lon_cappi_1500</span>: 401</li><li><span class='xr-has-index'>x_cappi_1500</span>: 401</li><li><span class='xr-has-index'>y_cappi_1500</span>: 401</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-25c268ed-d8d9-49f4-9f79-f2d6e3801845' class='xr-section-summary-in' type='checkbox'  checked><label for='section-25c268ed-d8d9-49f4-9f79-f2d6e3801845' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x_cappi_1500</span></div><div class='xr-var-dims'>(x_cappi_1500)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-200000 -199000 ... 199000 200000</div><input id='attrs-da06b714-1d82-464b-90b3-515895efb67f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da06b714-1d82-464b-90b3-515895efb67f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-59a2ccdf-b357-41e7-b233-a657ae68e713' class='xr-var-data-in' type='checkbox'><label for='data-59a2ccdf-b357-41e7-b233-a657ae68e713' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>CAPPI_product_x_axis </dd><dt><span>long_name :</span></dt><dd>east_distance_from_radar</dd><dt><span>axis :</span></dt><dd>xy_coordinate</dd><dt><span>comment :</span></dt><dd>Distance from radar in east</dd></dl></div><div class='xr-var-data'><pre>array([-200000, -199000, -198000, ...,  198000,  199000,  200000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y_cappi_1500</span></div><div class='xr-var-dims'>(y_cappi_1500)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-200000 -199000 ... 199000 200000</div><input id='attrs-47a74e65-d84c-4227-a308-7fda8328b4a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-47a74e65-d84c-4227-a308-7fda8328b4a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-110f8119-4167-43d6-b887-590984cacc8d' class='xr-var-data-in' type='checkbox'><label for='data-110f8119-4167-43d6-b887-590984cacc8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>meters</dd><dt><span>standard_name :</span></dt><dd>CAPPI_product_y_axis </dd><dt><span>long_name :</span></dt><dd>north_distance_from_radar</dd><dt><span>axis :</span></dt><dd>xy_coordinate</dd><dt><span>comment :</span></dt><dd>Distance from radar in north</dd></dl></div><div class='xr-var-data'><pre>array([-200000, -199000, -198000, ...,  198000,  199000,  200000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon_cappi_1500</span></div><div class='xr-var-dims'>(lon_cappi_1500)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>117.0 117.0 117.0 ... 121.0 121.0</div><input id='attrs-20c9686c-c88e-4cca-a862-7cc72384a6af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20c9686c-c88e-4cca-a862-7cc72384a6af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8f5e011a-0740-4a1b-af7e-2edcfb5be032' class='xr-var-data-in' type='checkbox'><label for='data-8f5e011a-0740-4a1b-af7e-2edcfb5be032' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>standard_name :</span></dt><dd>CAPPI_product_lon_axis </dd><dt><span>long_name :</span></dt><dd>longitude_CAPPI</dd><dt><span>axis :</span></dt><dd>lonlat_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([117.  , 117.01, 117.02, ..., 120.98, 120.99, 121.  ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat_cappi_1500</span></div><div class='xr-var-dims'>(lat_cappi_1500)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>28.0 28.01 28.02 ... 31.99 32.0</div><input id='attrs-05f9ccd2-7660-46e5-8bf8-ab858f2bcbb9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05f9ccd2-7660-46e5-8bf8-ab858f2bcbb9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9b0ae8c-5b30-4187-b4ea-d0ff47396dea' class='xr-var-data-in' type='checkbox'><label for='data-b9b0ae8c-5b30-4187-b4ea-d0ff47396dea' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees</dd><dt><span>standard_name :</span></dt><dd>CAPPI_product_lat_axis </dd><dt><span>long_name :</span></dt><dd>latitude_CAPPI</dd><dt><span>axis :</span></dt><dd>lonlat_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([28.  , 28.01, 28.02, ..., 31.98, 31.99, 32.  ])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6c5666af-d148-4dff-b424-1c94c33f7baf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6c5666af-d148-4dff-b424-1c94c33f7baf' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CAPPI_1500</span></div><div class='xr-var-dims'>(x_cappi_1500, y_cappi_1500)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-676469bc-8ff9-4c2e-a84e-2d3ef08eb147' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-676469bc-8ff9-4c2e-a84e-2d3ef08eb147' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e93d881-3fa9-4226-89d3-467a4f26ebbf' class='xr-var-data-in' type='checkbox'><label for='data-2e93d881-3fa9-4226-89d3-467a4f26ebbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>standard_name :</span></dt><dd>Constant_altitude_plan_position_indicator</dd><dt><span>long_name :</span></dt><dd>Constant_altitude_plan_position_indicator</dd><dt><span>axis :</span></dt><dd>xy_coordinate</dd><dt><span>comment :</span></dt><dd>CAPPI of level 1500 m.</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CAPPI_geo_1500</span></div><div class='xr-var-dims'>(lon_cappi_1500, lat_cappi_1500)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-1e9f9f26-4e33-45ba-b67b-bcec6192ccad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1e9f9f26-4e33-45ba-b67b-bcec6192ccad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33152d45-8322-489e-abe2-a7da324dea1d' class='xr-var-data-in' type='checkbox'><label for='data-33152d45-8322-489e-abe2-a7da324dea1d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>dBZ</dd><dt><span>standard_name :</span></dt><dd>Constant_altitude_plan_position_indicator</dd><dt><span>long_name :</span></dt><dd>Constant_altitude_plan_position_indicator</dd><dt><span>axis :</span></dt><dd>lonlat_coordinate</dd><dt><span>comment :</span></dt><dd>CAPPI of level 1500 m</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b3729b6-099b-4b9b-812c-4c9a3964e814' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1b3729b6-099b-4b9b-812c-4c9a3964e814' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:         (lat_cappi_1500: 401, lon_cappi_1500: 401, x_cappi_1500: 401, y_cappi_1500: 401)\n",
       "Coordinates:\n",
       "  * x_cappi_1500    (x_cappi_1500) int64 -200000 -199000 ... 199000 200000\n",
       "  * y_cappi_1500    (y_cappi_1500) int64 -200000 -199000 ... 199000 200000\n",
       "  * lon_cappi_1500  (lon_cappi_1500) float64 117.0 117.0 117.0 ... 121.0 121.0\n",
       "  * lat_cappi_1500  (lat_cappi_1500) float64 28.0 28.01 28.02 ... 31.99 32.0\n",
       "Data variables:\n",
       "    CAPPI_1500      (x_cappi_1500, y_cappi_1500) float64 nan nan nan ... nan nan\n",
       "    CAPPI_geo_1500  (lon_cappi_1500, lat_cappi_1500) float64 nan nan ... nan nan"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "PRD.product ##可查看lat lon坐标的cappi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "grid_lon, grid_lat = np.meshgrid(lon1d, lat1d, indexing=\"ij\")\n",
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "plot_lonlat_map(ax, grid_lon, grid_lat, PRD.product.CAPPI_geo_1500, transform=ccrs.PlateCarree())\n",
    "plt.show()##画图显示"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/zhengyu/anaconda3/envs/pycwr/lib/python3.9/site-packages/cartopy/mpl/geoaxes.py:1597: UserWarning: The input coordinates to pcolormesh are interpreted as cell centers, but are not monotonically increasing or decreasing. This may lead to incorrectly calculated cell edges, in which case, please supply explicit cell edges to pcolormesh.\n",
      "  X, Y, C, shading = self._pcolorargs('pcolormesh', *args,\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ax = plt.axes(projection=ccrs.PlateCarree())\n",
    "graph = GraphMap(PRD, ccrs.PlateCarree()) ##叠加地图\n",
    "graph.plot_ppi_map(ax, 0, \"dBZ\", cmap=\"CN_ref\") ## 0代表第一层, dBZ代表反射率产品\n",
    "ax.set_title(\"Using pycwr for ploting data with map\", fontsize=16)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
